The present invention relates to searching virtual resources, in particular, to searching virtual resources in a large scale computing system environment, e.g., a cloud computing environment.
Cloud computing is a novel style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of expertise in, or control over the technology infrastructure in the “cloud” that supports them. The majority of cloud computing infrastructure consists of reliable services delivered through data centers and built on servers with different levels of virtualization technologies. The services are accessible anywhere that provides access to networking infrastructure. Clouds often appear as single points of access for all consumers' computing needs.
FIG. 1 shows an example of a cloud computing center. In the example shown in FIG. 1, a plurality of interconnected servers 101 consist of a cloud computing center 100. A plurality of terminals 200 can access the cloud computing center 100 to get the computing services provided by the “cloud”. Such cloud computing center is already widely used in commercial area. For example, Amazon Elastic Compute Cloud (also known as “EC2”) is a commercial web service that allows customers to rent computers on which to run their own computer applications. EC2 allows scalable deployment of applications by providing a web services interface through which a customer can create virtual machines, i.e. server instances, on which the customer can load any software of their choice. A customer can create, launch, and terminate server instances as needed, paying by the hour for active servers, hence the term “elastic”. For further details of EC2, please refer to the Amazon Web Services (AWS) provided by Amazon.co. In addition, Azure Service Platform, which is provided by Microsoft, is also a cloud computing platform that provides a wide range of internet services, Microsoft and Salesforce, etc., each provides respective cloud computing services.
A cloud computing center is often implemented by a large number of physical servers which are collectively deployed at one or more data centers and are interconnected by networks. For example, a provider providing cloud computing services may implement one cloud computing center by deploying tens of thousands of physical servers within one data center.
In the above large scale cloud computing center, it is often required to find out the location of certain physical servers or certain virtual machines. For example, when one virtual machine providing cloud computing services for users does not work, the manager will want to find out the specific location of this virtual machine. In addition, for example, when a certain physical machine does not work, the manager will also want to find out the specific location of this physical machine.
However, physical servers of a cloud computing center are often moved to be re-deployed, thus the physical servers and the virtual machines thereon will be often moved. Even if the manager carefully records the new location information after every movement of the physical servers, when the number of movements is bigger and bigger, it is still easy for the manager to make mistakes and thus lose the location information of certain physical machine. Moreover, it is also a big burden for the manager to record and update the location of every physical server, in particular, when the data center is of a very large scale, it is a mission impossible. For example, according to a report from one large data center, a significant percentage of the physical servers in this data center cannot be precisely located, though the overall cloud computing center still operates.
In the cloud computing center, not only the location of physical servers is frequently moved, the virtual machines on the physical servers are often dynamically established, moved, and merged, etc. Therefore, the locations of both physical machines and virtual machine are constantly changed, thus it is difficult to provide a satisfying location service by the means of the prior art.
For example, U.S. Pat. No. 7,180,422 discloses an asset management method and device, wherein a logical tag (L-tag) and a physical tag (P-tag) are attached to a target device in order to manage the target device. The physical tag includes the physical address information of the computer and other information, the logical tag includes the name, the IP address, etc. of the computer. RFID is used as the tag. However, the above method can merely track the physical and logical attributes of physical computers; hut cannot be applied to virtual servers and cannot provide any information of virtual servers. Further, since RFID is used for the tags, additional RFID reader is required, and the distance between the reader and RFID is limited, thus the operating distance of the above method is limited.
Further, for example, U.S. Pat. No. 7,436,303 describes a rack sensor controller operable to sense information for hardware assets housed in a rack. Each rack sensor controller has a memory storing a location of the rack and sensor information received from a plurality of sensors. At least some of the sensors include one or more RFID readers operable to read RFID tags attached to assets housed in the rack. Each rack sensor controller has a processor, which is operable to receive the sensor information and generate a message including the sensor information and the location of the rack for transmission to one or more back-end applications via a forwarder. However, in the above patent, the sensors are mounted on racks, and the locations of racks are relatively fixed and are not frequently moved. Thus this patent cannot be applied to a dynamic data computing environment where the servers are arbitrarily moved, for example, physical servers of a cloud computing center can be moved. Further, the above patent uses RFID techniques. Each REID is passive and does not have communicating or computing capabilities. Thus additional RFID reader is required, and the above device is limited by a communication distance of the RFID reader.